IDEAS home Printed from https://ideas.repec.org/a/wsi/qjfxxx/v13y2023i01ns2010139223500039.html
   My bibliography  Save this article

Two Different Exits: Prediction and Performance of Stocks that are About to Stop Trading

Author

Listed:
  • Ting Bai

    (University of California, Davis, USA)

  • Jens Hilscher

    (University of California, Davis, USA)

  • Yitian Xiao

    (Mingshi Investment, 488 Middle Yincheng Road, Shanghai, China)

Abstract

This paper predicts the two most common stock market exits — mergers and drops — using logit models based on firm-level variables and analyzes the returns of stocks that have high exit probabilities. Such analysis is important for investors given that frequent exits are partly responsible for the large US listing gap (Doidge et al., 2017). High merger probability stocks have positive 3-factor alphas and lower-than-average volatility. Firms with high drop probabilities have anomalously negative 3-, 4-, and 5-factor alphas between −1.8% and −4% per month. Results are robust to controlling for the effects of skewness, volatility, and turnover on returns.

Suggested Citation

  • Ting Bai & Jens Hilscher & Yitian Xiao, 2023. "Two Different Exits: Prediction and Performance of Stocks that are About to Stop Trading," Quarterly Journal of Finance (QJF), World Scientific Publishing Co. Pte. Ltd., vol. 13(01), pages 1-28, March.
  • Handle: RePEc:wsi:qjfxxx:v:13:y:2023:i:01:n:s2010139223500039
    DOI: 10.1142/S2010139223500039
    as

    Download full text from publisher

    File URL: http://www.worldscientific.com/doi/abs/10.1142/S2010139223500039
    Download Restriction: Access to full text is restricted to subscribers

    File URL: https://libkey.io/10.1142/S2010139223500039?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:wsi:qjfxxx:v:13:y:2023:i:01:n:s2010139223500039. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Tai Tone Lim (email available below). General contact details of provider: http://www.worldscinet.com/qjf/qjf.shtml .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.